The invention relates generally to the use of adaptive antenna arrays in digital radio communications and, more particularly, to angle-of-arrival (AOA) estimation for downlink use in such adaptive antenna arrays.
In array signal processing of digital communications, an array of receive and transmit antennas is deployed in the base station (e.g. in a cellular telephone network) to combat interference and in that way increase capacity and performance of the system. There are two main concepts for exploiting the potential performance gain from an antenna array.
One approach is to use the antenna to form a number of fixed beams in the uplink. The receiver algorithm then uses the output from one or more beams to receive a desired user. In the downlink, the data is then transmitted in the beam with the highest signal-to-noise ratio (SNR), or in several beams in the case of transmit diversity systems.
Another possibility is to steer a narrow beam directly towards a desired mobile. This can be done in two fundamentally different ways.
In a parametric approach, the angles-of-arrival of the multipaths (fingers) of the desired user are explicitly estimated, and the uplink beams are then steered in the determined direction. The AOA giving the highest SNR is then used for the downlink transmission. Again, in the case of transmit diversity, several downlink beams can be utilized.
In a non-parametric approach, the AOAs of the desired user are not estimated explicitly, but only the spatial channels (or spatial signatures) are estimated, giving rise to an estimated array weight vector (obtained for example using a vector RAKE receiver) for each finger. The combination of these weights applied to the array output yields the signal used to receive the user data. The non-parametric methods do not yield any explicit information on the AOAs for the user, and these AOAs have to be estimated separately.
There is much scientific literature on AOA estimation using adaptive antennas. The interest in AOA estimation was mainly spurred by the advent of the so-called super-resolution algorithms, such as MUSIC, ESPRIT, MODE and WSF, methods that can estimate the AOAs with higher accuracy than the classical beamforming algorithms.
One of the major shortcomings of the popular super-resolution methods is their computational complexity. They often involve performing the singular value decomposition of a matrix the size of the array. Another drawback of these methods is their reported sensitivity to model errors; their ability to give good estimates of the AOAs relies heavily on a parametric model of the signal environment and an accurate calibration of the antenna array.
The non-parametric methods, such as beamforming, basically work by scanning the area covered by the array with a narrow beam and selecting the AOA as the direction giving the highest output power from the array. As such, these methods are more robust, but their bad resolution can be a limiting factor in practice, where many users are present close to each other and where noise levels might be high.
It is desirable in view of the foregoing to provide for AOA estimation without the aforementioned disadvantages of the prior art approaches.
In an attempt to avoid the aforementioned disadvantages of the prior art approaches, the present invention exploits a characteristic of conventionally available uplink weight vectors used in antenna arrays having a shift invariance structure, and calculates AOA estimates directly from the uplink weight vectors.